The present invention relates generally to digital image processing techniques and in particular to a method and apparatus for calibrating a non-contact range sensor of the type used to obtain digital images of objects for the purpose of inspecting the objects for defects.
Currently, automated inspection is performed on manufactured objects such as airfoils (e.g. turbine blades) by obtaining digital data and images of the objects to detect defects in them. Airfoils, including forged blades such as those used for aircraft engines, are inspected for deformation parameters such as platform orientation, contour cross-section, bow and twist along stacking axis, thickness and chord length at given cross-sections. One method of obtaining digital data representing these parameters is through coordinate measurement machines (commonly known as xe2x80x9cCMMsxe2x80x9d). CMM""s translate and rotate a probe in contact with the surface of the object to sample points on the object""s surface.
Another means of obtaining digital representations of these parameters is with full-field non-contact range sensors. Non-contact full-field sensors scan the external surfaces of opaque objects using laser or white light. These sensors are capable of scanning the part quickly while obtaining large quantities of data. Examples of non contact sensors include sensors that are based on laser line grating and stereo triangulation; and based on single laser line scan plus rotating the part. Another non contact sensor is based on phased-shift Moirxc3xa9 and white light.
The raw data points obtained by non-contact sensors, however, provide a very low degree of accuracy and thereby, generate noisy normal deviations that yield unacceptable precision and accuracy when the data are used to reconstruct the surface of an object in order to detect deformations and defects of the object. Because full-field sensors are relatively new, efforts to calibrate and characterize them to increase their accuracy have been few and largely unsuccessful.
In an exemplary embodiment of the present invention, a method for calibrating a non contact range sensor comprises the steps of scanning the object to be inspected with the range sensor to obtain a range image of the object. The range image is registered with a reference image of the object to provide registered data. Normal deviations between the registered data and the reference image are computed. Noise is filtered from the normal deviations. A plurality of bias vectors and a covariance matrix are estimated and used to generate a lookup table comprising geometric correction factors. The range image of the object is compensated in accordance with the lookup table.